Face Detection Algorithm Based On Region, Gabor Filtering, And Color Characteristics

With the expanding application areas and the increasing requirement in practical systems, the face detection has been developed as an independent subject, and has played a significant role in many fields, for example, new man-machine interface, content-based video retrieval and visual supervise and so on.Facing video image sequences with complex background, this paper comes up with the face detection algorithm based on the techniques of skin-color, region morphology, Gabor wavelet and Support Vector Machine (SVM), and gets the satisfactory detection result. There are three steps of the concrete process of the algorithm: initial localization, separating image and confirmation. Firstly, single Gaussian model is used to imitate skin-color distribution, meanwhile, skin probability images which is smoothly disposed using middle wave is calculated to attain the initial localization. Secondly, in order to separate the latent face region, it uses multimodal information that includes the region growing,the hue and brightness,skin probability images etc. At last, it adopts the criterion of morphology analysis and face characteristic draw to confirm the latent region.The algorithm in this paper can detect multi faces with multiple orientation and scales against a complex background. It is robust in the use of external effects such as illumination difference, pose diversity, face rotation and face expression, at the same time , it maintains the outline of face margin, and favor the ability of real-time,detection rate and anti-noise.